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A Genetically Informed Study of the Associations Between Maternal Age at Childbearing and Adverse Perinatal Outcomes
Department of Psychological and Brain Sciences, Indiana University, Bloomington, USA.
Department of Psychological and Brain Sciences, Indiana University, Bloomington, USA.
Department of Psychological and Brain Sciences, Indiana University, Bloomington, USA.
Ann and Robert H. Lurie Children’s Hospital, Chicago, USA.
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2016 (English)In: Behavior Genetics, ISSN 0001-8244, E-ISSN 1573-3297, Vol. 46, no 3, p. 431-456Article in journal (Refereed) Published
Abstract [en]

We examined associations of maternal age at childbearing (MAC) with gestational age and fetal growth (i.e., birth weight adjusting for gestational age), using two genetically informed designs (cousin and sibling comparisons) and data from two cohorts, a population-based Swedish sample and a nationally representative United States sample. We also conducted sensitivity analyses to test limitations of the designs. The findings were consistent across samples and suggested that, associations observed in the population between younger MAC and shorter gestational age were confounded by shared familial factors; however, associations of advanced MAC with shorter gestational age remained robust after accounting for shared familial factors. In contrast to the gestational age findings, neither early nor advanced MAC was associated with lower fetal growth after accounting for shared familial factors. Given certain assumptions, these findings provide support for a causal association between advanced MAC and shorter gestational age. The results also suggest that there are not causal associations between early MAC and shorter gestational age, between early MAC and lower fetal growth, and between advanced MAC and lower fetal growth.

Place, publisher, year, edition, pages
New York, USA: Springer, 2016. Vol. 46, no 3, p. 431-456
Keywords [en]
Gestational age, birth weight, fetal growth, maternal age at childbearing, genetically informed designs, quasi-experiments
National Category
Medical and Health Sciences Genetics Psychology
Identifiers
URN: urn:nbn:se:oru:diva-54620DOI: 10.1007/s10519-015-9748-0ISI: 000375616400013PubMedID: 26404627Scopus ID: 2-s2.0-84944539641OAI: oai:DiVA.org:oru-54620DiVA, id: diva2:1064465
Note

Funding Agencies:

National Science Foundation 

Swedish Initiative for Research on Microdata in the Social And Medical Sciences (SIMSAM)

National Institute of Child Health and Human Development

Available from: 2017-01-12 Created: 2017-01-12 Last updated: 2018-07-23Bibliographically approved

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Larsson, Henrik

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